Overview

Dataset statistics

Number of variables16
Number of observations528870
Missing cells20514
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory64.6 MiB
Average record size in memory128.0 B

Variable types

Numeric11
Categorical4
DateTime1

Alerts

beer_name has a high cardinality: 18339 distinct values High cardinality
beer_style has a high cardinality: 104 distinct values High cardinality
review_profileName has a high cardinality: 22800 distinct values High cardinality
review_text has a high cardinality: 528371 distinct values High cardinality
review_appearance is highly correlated with review_tasteHigh correlation
review_palette is highly correlated with review_overall and 2 other fieldsHigh correlation
review_overall is highly correlated with review_palette and 2 other fieldsHigh correlation
review_taste is highly correlated with review_appearance and 3 other fieldsHigh correlation
review_aroma is highly correlated with review_palette and 2 other fieldsHigh correlation
review_appearance is highly correlated with review_palette and 2 other fieldsHigh correlation
review_palette is highly correlated with review_appearance and 3 other fieldsHigh correlation
review_overall is highly correlated with review_palette and 2 other fieldsHigh correlation
review_taste is highly correlated with review_appearance and 3 other fieldsHigh correlation
review_aroma is highly correlated with review_appearance and 3 other fieldsHigh correlation
review_palette is highly correlated with review_aromaHigh correlation
review_overall is highly correlated with review_taste and 1 other fieldsHigh correlation
review_taste is highly correlated with review_overall and 1 other fieldsHigh correlation
review_aroma is highly correlated with review_palette and 2 other fieldsHigh correlation
beer_beerId is highly correlated with beer_brewerId and 1 other fieldsHigh correlation
beer_brewerId is highly correlated with beer_beerIdHigh correlation
review_appearance is highly correlated with review_palette and 3 other fieldsHigh correlation
review_palette is highly correlated with review_appearance and 3 other fieldsHigh correlation
review_overall is highly correlated with review_appearance and 3 other fieldsHigh correlation
review_taste is highly correlated with review_appearance and 3 other fieldsHigh correlation
review_aroma is highly correlated with review_appearance and 3 other fieldsHigh correlation
review_year is highly correlated with beer_beerIdHigh correlation
beer_ABV has 20280 (3.8%) missing values Missing
review_text is uniformly distributed Uniform
review_hr has 43762 (8.3%) zeros Zeros

Reproduction

Analysis started2022-07-29 13:58:35.243316
Analysis finished2022-07-29 14:02:52.239888
Duration4 minutes and 17 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

beer_ABV
Real number (ℝ≥0)

MISSING

Distinct283
Distinct (%)0.1%
Missing20280
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean7.017441593
Minimum0.01
Maximum57.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 MiB
2022-07-29T19:32:52.351530image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile4.5
Q15.3
median6.5
Q38.5
95-th percentile11
Maximum57.7
Range57.69
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation2.204459957
Coefficient of variation (CV)0.3141401218
Kurtosis6.853875212
Mean7.017441593
Median Absolute Deviation (MAD)1.5
Skewness1.459241165
Sum3569000.62
Variance4.859643701
MonotonicityNot monotonic
2022-07-29T19:32:52.481222image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
538935
 
7.4%
5.522213
 
4.2%
921319
 
4.0%
820831
 
3.9%
620725
 
3.9%
6.517028
 
3.2%
716496
 
3.1%
1014087
 
2.7%
7.513992
 
2.6%
9.513739
 
2.6%
Other values (273)309225
58.5%
(Missing)20280
 
3.8%
ValueCountFrequency (%)
0.013
 
< 0.1%
0.0511
 
< 0.1%
0.14
 
< 0.1%
0.32
 
< 0.1%
0.431
< 0.1%
0.576
< 0.1%
0.92
 
< 0.1%
12
 
< 0.1%
1.220
 
< 0.1%
1.41
 
< 0.1%
ValueCountFrequency (%)
57.71
 
< 0.1%
432
 
< 0.1%
39.443
 
< 0.1%
30.861
 
< 0.1%
27355
0.1%
2531
 
< 0.1%
2420
 
< 0.1%
2122
 
< 0.1%
19.522
 
< 0.1%
19.21
 
< 0.1%

beer_beerId
Real number (ℝ≥0)

HIGH CORRELATION

Distinct20200
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22098.46602
Minimum3
Maximum77310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 MiB
2022-07-29T19:32:52.634151image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile159
Q11745
median14368
Q340528
95-th percentile63166
Maximum77310
Range77307
Interquartile range (IQR)38783

Descriptive statistics

Standard deviation22158.28435
Coefficient of variation (CV)1.0027069
Kurtosis-0.8925518348
Mean22098.46602
Median Absolute Deviation (MAD)13720
Skewness0.6723067969
Sum1.168721572 × 1010
Variance490989565.4
MonotonicityNot monotonic
2022-07-29T19:32:52.777085image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19043000
 
0.6%
2762587
 
0.5%
117572502
 
0.5%
26712492
 
0.5%
342483
 
0.5%
1042418
 
0.5%
3552234
 
0.4%
6452170
 
0.4%
304202029
 
0.4%
5712025
 
0.4%
Other values (20190)504930
95.5%
ValueCountFrequency (%)
33
 
< 0.1%
410
 
< 0.1%
5424
0.1%
6877
0.2%
7659
0.1%
868
 
< 0.1%
9116
 
< 0.1%
1185
 
< 0.1%
1286
 
< 0.1%
1384
 
< 0.1%
ValueCountFrequency (%)
773101
< 0.1%
773071
< 0.1%
773051
< 0.1%
773031
< 0.1%
773021
< 0.1%
772981
< 0.1%
772971
< 0.1%
772951
< 0.1%
772811
< 0.1%
772481
< 0.1%

beer_brewerId
Real number (ℝ≥0)

HIGH CORRELATION

Distinct1803
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2598.423429
Minimum1
Maximum27980
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 MiB
2022-07-29T19:32:52.918987image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile35
Q1132
median394
Q31475
95-th percentile16866
Maximum27980
Range27979
Interquartile range (IQR)1343

Descriptive statistics

Standard deviation5281.80535
Coefficient of variation (CV)2.032696169
Kurtosis5.57860685
Mean2598.423429
Median Absolute Deviation (MAD)326
Skewness2.55988546
Sum1374228199
Variance27897467.75
MonotonicityNot monotonic
2022-07-29T19:32:53.043813image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3539444
 
7.5%
14028751
 
5.4%
13224083
 
4.6%
119920004
 
3.8%
381815868
 
3.0%
15814935
 
2.8%
2213921
 
2.6%
19213410
 
2.5%
39212248
 
2.3%
69411842
 
2.2%
Other values (1793)334364
63.2%
ValueCountFrequency (%)
11357
 
0.3%
240
 
< 0.1%
35357
 
1.0%
5728
 
0.1%
1056
 
< 0.1%
141202
 
0.2%
2213921
 
2.6%
31754
 
0.1%
3539444
7.5%
36316
 
0.1%
ValueCountFrequency (%)
279803
 
< 0.1%
279223
 
< 0.1%
279171
 
< 0.1%
278793
 
< 0.1%
278704
< 0.1%
278082
 
< 0.1%
277976
< 0.1%
277933
 
< 0.1%
276451
 
< 0.1%
276329
< 0.1%

beer_name
Categorical

HIGH CARDINALITY

Distinct18339
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size4.0 MiB
Sierra Nevada Celebration Ale
 
3000
Sierra Nevada Pale Ale
 
2587
Founders Breakfast Stout
 
2502
Sierra Nevada Bigfoot Barleywine Style Ale
 
2492
La Fin Du Monde
 
2483
Other values (18334)
515806 

Length

Max length75
Median length64
Mean length21.65885
Min length1

Characters and Unicode

Total characters11454716
Distinct characters137
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6143 ?
Unique (%)1.2%

Sample

1st rowSausa Weizen
2nd rowRed Moon
3rd rowBlack Horse Black Beer
4th rowSausa Pils
5th rowCauldron DIPA

Common Values

ValueCountFrequency (%)
Sierra Nevada Celebration Ale3000
 
0.6%
Sierra Nevada Pale Ale2587
 
0.5%
Founders Breakfast Stout2502
 
0.5%
Sierra Nevada Bigfoot Barleywine Style Ale2492
 
0.5%
La Fin Du Monde2483
 
0.5%
Samuel Adams Boston Lager2418
 
0.5%
Chocolate Stout2254
 
0.4%
Dead Guy Ale2234
 
0.4%
Trappistes Rochefort 102170
 
0.4%
Sierra Nevada Torpedo Extra IPA2029
 
0.4%
Other values (18329)504701
95.4%

Length

2022-07-29T19:32:53.449532image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ale139829
 
7.7%
stout51762
 
2.8%
samuel42947
 
2.4%
imperial38745
 
2.1%
ipa35313
 
1.9%
pale34081
 
1.9%
adams33495
 
1.8%
porter22522
 
1.2%
lager22422
 
1.2%
21640
 
1.2%
Other values (12191)1377242
75.7%

Most occurring characters

ValueCountFrequency (%)
1291763
 
11.3%
e1273753
 
11.1%
a776637
 
6.8%
r725066
 
6.3%
l607507
 
5.3%
t553240
 
4.8%
o528262
 
4.6%
i519545
 
4.5%
n411256
 
3.6%
s383822
 
3.4%
Other values (127)4383865
38.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7945520
69.4%
Uppercase Letter1903124
 
16.6%
Space Separator1291781
 
11.3%
Decimal Number103835
 
0.9%
Other Punctuation83977
 
0.7%
Open Punctuation45531
 
0.4%
Close Punctuation45531
 
0.4%
Dash Punctuation33916
 
0.3%
Other Symbol727
 
< 0.1%
Math Symbol351
 
< 0.1%
Other values (4)423
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1273753
16.0%
a776637
9.8%
r725066
 
9.1%
l607507
 
7.6%
t553240
 
7.0%
o528262
 
6.6%
i519545
 
6.5%
n411256
 
5.2%
s383822
 
4.8%
u331956
 
4.2%
Other values (42)1834476
23.1%
Uppercase Letter
ValueCountFrequency (%)
A281435
14.8%
S256572
13.5%
B172039
 
9.0%
P151015
 
7.9%
I109450
 
5.8%
C89843
 
4.7%
D85904
 
4.5%
H84041
 
4.4%
R76104
 
4.0%
L75748
 
4.0%
Other values (30)520973
27.4%
Other Punctuation
ValueCountFrequency (%)
'44832
53.4%
.21067
25.1%
#4565
 
5.4%
/3412
 
4.1%
&2960
 
3.5%
:2127
 
2.5%
,1993
 
2.4%
%1636
 
1.9%
"674
 
0.8%
?306
 
0.4%
Other values (3)405
 
0.5%
Decimal Number
ValueCountFrequency (%)
029238
28.2%
118079
17.4%
215746
15.2%
58920
 
8.6%
47030
 
6.8%
86158
 
5.9%
95225
 
5.0%
35131
 
4.9%
64274
 
4.1%
74034
 
3.9%
Control
ValueCountFrequency (%)
’82
30.5%
ž78
29.0%
Ž49
18.2%
š37
13.8%
Š16
 
5.9%
–5
 
1.9%
‘2
 
0.7%
Space Separator
ValueCountFrequency (%)
1291763
> 99.9%
 18
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
(45009
98.9%
[522
 
1.1%
Close Punctuation
ValueCountFrequency (%)
)45009
98.9%
]522
 
1.1%
Math Symbol
ValueCountFrequency (%)
+347
98.9%
=4
 
1.1%
Other Number
ValueCountFrequency (%)
³138
99.3%
½1
 
0.7%
Modifier Symbol
ValueCountFrequency (%)
´5
83.3%
^1
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
-33916
100.0%
Other Symbol
ValueCountFrequency (%)
°727
100.0%
Other Letter
ValueCountFrequency (%)
º9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9848653
86.0%
Common1606063
 
14.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1273753
 
12.9%
a776637
 
7.9%
r725066
 
7.4%
l607507
 
6.2%
t553240
 
5.6%
o528262
 
5.4%
i519545
 
5.3%
n411256
 
4.2%
s383822
 
3.9%
u331956
 
3.4%
Other values (83)3737609
38.0%
Common
ValueCountFrequency (%)
1291763
80.4%
(45009
 
2.8%
)45009
 
2.8%
'44832
 
2.8%
-33916
 
2.1%
029238
 
1.8%
.21067
 
1.3%
118079
 
1.1%
215746
 
1.0%
58920
 
0.6%
Other values (34)52484
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII11417813
99.7%
None36903
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1291763
 
11.3%
e1273753
 
11.2%
a776637
 
6.8%
r725066
 
6.4%
l607507
 
5.3%
t553240
 
4.8%
o528262
 
4.6%
i519545
 
4.6%
n411256
 
3.6%
s383822
 
3.4%
Other values (73)4346962
38.1%
None
ValueCountFrequency (%)
é11566
31.3%
ö8741
23.7%
è4303
 
11.7%
ä2511
 
6.8%
ü2186
 
5.9%
É2073
 
5.6%
°727
 
2.0%
ø620
 
1.7%
á552
 
1.5%
Ü510
 
1.4%
Other values (44)3114
 
8.4%

beer_style
Categorical

HIGH CARDINALITY

Distinct104
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.0 MiB
American IPA
43369 
American Double / Imperial IPA
 
26106
American Double / Imperial Stout
 
23354
American Pale Ale (APA)
 
20520
American Amber / Red Ale
 
18731
Other values (99)
396790 

Length

Max length35
Median length26
Mean length17.84279691
Min length4

Characters and Unicode

Total characters9436520
Distinct characters58
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHefeweizen
2nd rowEnglish Strong Ale
3rd rowForeign / Export Stout
4th rowGerman Pilsener
5th rowAmerican Double / Imperial IPA

Common Values

ValueCountFrequency (%)
American IPA43369
 
8.2%
American Double / Imperial IPA26106
 
4.9%
American Double / Imperial Stout23354
 
4.4%
American Pale Ale (APA)20520
 
3.9%
American Amber / Red Ale18731
 
3.5%
Russian Imperial Stout17192
 
3.3%
American Porter16601
 
3.1%
Belgian Strong Dark Ale15407
 
2.9%
Fruit / Vegetable Beer15148
 
2.9%
Witbier13535
 
2.6%
Other values (94)318907
60.3%

Length

2022-07-29T19:32:53.603278image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
american218741
 
13.9%
ale162249
 
10.3%
138598
 
8.8%
ipa77685
 
4.9%
imperial68912
 
4.4%
pale64758
 
4.1%
stout62647
 
4.0%
double51720
 
3.3%
belgian38454
 
2.4%
strong38391
 
2.4%
Other values (114)648220
41.3%

Most occurring characters

ValueCountFrequency (%)
e1148110
 
12.2%
1041505
 
11.0%
r692365
 
7.3%
a620628
 
6.6%
i580603
 
6.2%
l561885
 
6.0%
A535132
 
5.7%
n479963
 
5.1%
m354413
 
3.8%
t335046
 
3.6%
Other values (48)3086870
32.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6551914
69.4%
Uppercase Letter1635627
 
17.3%
Space Separator1041505
 
11.0%
Other Punctuation134125
 
1.4%
Close Punctuation34438
 
0.4%
Open Punctuation34438
 
0.4%
Dash Punctuation4473
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1148110
17.5%
r692365
10.6%
a620628
9.5%
i580603
8.9%
l561885
8.6%
n479963
7.3%
m354413
 
5.4%
t335046
 
5.1%
c307986
 
4.7%
o281061
 
4.3%
Other values (19)1189854
18.2%
Uppercase Letter
ValueCountFrequency (%)
A535132
32.7%
P205323
 
12.6%
I156022
 
9.5%
S139570
 
8.5%
B135887
 
8.3%
D91980
 
5.6%
R53425
 
3.3%
E52582
 
3.2%
L48028
 
2.9%
W47896
 
2.9%
Other values (13)169782
 
10.4%
Other Punctuation
ValueCountFrequency (%)
/133847
99.8%
&278
 
0.2%
Space Separator
ValueCountFrequency (%)
1041505
100.0%
Close Punctuation
ValueCountFrequency (%)
)34438
100.0%
Open Punctuation
ValueCountFrequency (%)
(34438
100.0%
Dash Punctuation
ValueCountFrequency (%)
-4473
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8187541
86.8%
Common1248979
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1148110
14.0%
r692365
 
8.5%
a620628
 
7.6%
i580603
 
7.1%
l561885
 
6.9%
A535132
 
6.5%
n479963
 
5.9%
m354413
 
4.3%
t335046
 
4.1%
c307986
 
3.8%
Other values (42)2571410
31.4%
Common
ValueCountFrequency (%)
1041505
83.4%
/133847
 
10.7%
)34438
 
2.8%
(34438
 
2.8%
-4473
 
0.4%
&278
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII9424535
99.9%
None11985
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e1148110
 
12.2%
1041505
 
11.1%
r692365
 
7.3%
a620628
 
6.6%
i580603
 
6.2%
l561885
 
6.0%
A535132
 
5.7%
n479963
 
5.1%
m354413
 
3.8%
t335046
 
3.6%
Other values (45)3074885
32.6%
None
ValueCountFrequency (%)
ä7012
58.5%
è2631
 
22.0%
ö2342
 
19.5%

review_appearance
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.864522472
Minimum0
Maximum5
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size4.0 MiB
2022-07-29T19:32:53.713439image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q13.5
median4
Q34
95-th percentile4.5
Maximum5
Range5
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.6040104277
Coefficient of variation (CV)0.1562962648
Kurtosis1.646281704
Mean3.864522472
Median Absolute Deviation (MAD)0.5
Skewness-0.859660346
Sum2043830
Variance0.3648285968
MonotonicityNot monotonic
2022-07-29T19:32:53.812342image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4226081
42.7%
3.5103728
19.6%
4.5100536
19.0%
353194
 
10.1%
523107
 
4.4%
2.512258
 
2.3%
27513
 
1.4%
1.51616
 
0.3%
1834
 
0.2%
03
 
< 0.1%
ValueCountFrequency (%)
03
 
< 0.1%
1834
 
0.2%
1.51616
 
0.3%
27513
 
1.4%
2.512258
 
2.3%
353194
 
10.1%
3.5103728
19.6%
4226081
42.7%
4.5100536
19.0%
523107
 
4.4%
ValueCountFrequency (%)
523107
 
4.4%
4.5100536
19.0%
4226081
42.7%
3.5103728
19.6%
353194
 
10.1%
2.512258
 
2.3%
27513
 
1.4%
1.51616
 
0.3%
1834
 
0.2%
03
 
< 0.1%

review_palette
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.758925634
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 MiB
2022-07-29T19:32:53.907874image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q13.5
median4
Q34
95-th percentile4.5
Maximum5
Range4
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.6853348638
Coefficient of variation (CV)0.1823220065
Kurtosis1.153050129
Mean3.758925634
Median Absolute Deviation (MAD)0.5
Skewness-0.8261567139
Sum1987983
Variance0.4696838755
MonotonicityNot monotonic
2022-07-29T19:32:54.000768image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4188463
35.6%
3.5120100
22.7%
4.593923
17.8%
364623
 
12.2%
522320
 
4.2%
2.520936
 
4.0%
213024
 
2.5%
1.53579
 
0.7%
11902
 
0.4%
ValueCountFrequency (%)
11902
 
0.4%
1.53579
 
0.7%
213024
 
2.5%
2.520936
 
4.0%
364623
 
12.2%
3.5120100
22.7%
4188463
35.6%
4.593923
17.8%
522320
 
4.2%
ValueCountFrequency (%)
522320
 
4.2%
4.593923
17.8%
4188463
35.6%
3.5120100
22.7%
364623
 
12.2%
2.520936
 
4.0%
213024
 
2.5%
1.53579
 
0.7%
11902
 
0.4%

review_overall
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.833197194
Minimum0
Maximum5
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size4.0 MiB
2022-07-29T19:32:54.102352image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.5
Q13.5
median4
Q34.5
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7099617749
Coefficient of variation (CV)0.1852139973
Kurtosis1.69807555
Mean3.833197194
Median Absolute Deviation (MAD)0.5
Skewness-1.029727209
Sum2027263
Variance0.5040457218
MonotonicityNot monotonic
2022-07-29T19:32:54.198822image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4196544
37.2%
4.5110928
21.0%
3.598901
18.7%
353707
 
10.2%
531028
 
5.9%
2.518539
 
3.5%
211931
 
2.3%
1.53996
 
0.8%
13293
 
0.6%
03
 
< 0.1%
ValueCountFrequency (%)
03
 
< 0.1%
13293
 
0.6%
1.53996
 
0.8%
211931
 
2.3%
2.518539
 
3.5%
353707
 
10.2%
3.598901
18.7%
4196544
37.2%
4.5110928
21.0%
531028
 
5.9%
ValueCountFrequency (%)
531028
 
5.9%
4.5110928
21.0%
4196544
37.2%
3.598901
18.7%
353707
 
10.2%
2.518539
 
3.5%
211931
 
2.3%
1.53996
 
0.8%
13293
 
0.6%
03
 
< 0.1%

review_taste
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.765992588
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 MiB
2022-07-29T19:32:54.299980image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q13.5
median4
Q34
95-th percentile4.5
Maximum5
Range4
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.6690176237
Coefficient of variation (CV)0.1776470899
Kurtosis1.302840159
Mean3.765992588
Median Absolute Deviation (MAD)0.5
Skewness-0.8521780183
Sum1991720.5
Variance0.4475845809
MonotonicityNot monotonic
2022-07-29T19:32:54.399637image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4205951
38.9%
3.5110996
21.0%
4.586918
16.4%
366954
 
12.7%
521648
 
4.1%
2.519647
 
3.7%
211732
 
2.2%
1.53184
 
0.6%
11840
 
0.3%
ValueCountFrequency (%)
11840
 
0.3%
1.53184
 
0.6%
211732
 
2.2%
2.519647
 
3.7%
366954
 
12.7%
3.5110996
21.0%
4205951
38.9%
4.586918
16.4%
521648
 
4.1%
ValueCountFrequency (%)
521648
 
4.1%
4.586918
16.4%
4205951
38.9%
3.5110996
21.0%
366954
 
12.7%
2.519647
 
3.7%
211732
 
2.2%
1.53184
 
0.6%
11840
 
0.3%

review_profileName
Categorical

HIGH CARDINALITY

Distinct22800
Distinct (%)4.3%
Missing115
Missing (%)< 0.1%
Memory size4.0 MiB
northyorksammy
 
1858
mikesgroove
 
1403
BuckeyeNation
 
1298
womencantsail
 
1238
Phyl21ca
 
1164
Other values (22795)
521794 

Length

Max length16
Median length13
Mean length8.969307146
Min length3

Characters and Unicode

Total characters4742566
Distinct characters63
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7698 ?
Unique (%)1.5%

Sample

1st rowstcules
2nd rowstcules
3rd rowstcules
4th rowstcules
5th rowjohnmichaelsen

Common Values

ValueCountFrequency (%)
northyorksammy1858
 
0.4%
mikesgroove1403
 
0.3%
BuckeyeNation1298
 
0.2%
womencantsail1238
 
0.2%
Phyl21ca1164
 
0.2%
ChainGangGuy1155
 
0.2%
Thorpe4291042
 
0.2%
brentk561026
 
0.2%
NeroFiddled1012
 
0.2%
feloniousmonk1008
 
0.2%
Other values (22790)516551
97.7%

Length

2022-07-29T19:32:54.532648image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
northyorksammy1858
 
0.4%
mikesgroove1403
 
0.3%
buckeyenation1298
 
0.2%
womencantsail1238
 
0.2%
phyl21ca1164
 
0.2%
chaingangguy1155
 
0.2%
thorpe4291042
 
0.2%
brentk561026
 
0.2%
nerofiddled1012
 
0.2%
feloniousmonk1008
 
0.2%
Other values (22790)516551
97.7%

Most occurring characters

ValueCountFrequency (%)
e483062
 
10.2%
a352741
 
7.4%
r334889
 
7.1%
o287844
 
6.1%
n255802
 
5.4%
i241118
 
5.1%
t210878
 
4.4%
s200749
 
4.2%
l189968
 
4.0%
d147651
 
3.1%
Other values (53)2037864
43.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3970614
83.7%
Uppercase Letter451480
 
9.5%
Decimal Number320146
 
6.8%
Dash Punctuation326
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e483062
 
12.2%
a352741
 
8.9%
r334889
 
8.4%
o287844
 
7.2%
n255802
 
6.4%
i241118
 
6.1%
t210878
 
5.3%
s200749
 
5.1%
l189968
 
4.8%
d147651
 
3.7%
Other values (16)1265912
31.9%
Uppercase Letter
ValueCountFrequency (%)
B55361
 
12.3%
S33700
 
7.5%
M30977
 
6.9%
D30483
 
6.8%
T27242
 
6.0%
C26883
 
6.0%
G24273
 
5.4%
J21692
 
4.8%
R21157
 
4.7%
A21048
 
4.7%
Other values (16)158664
35.1%
Decimal Number
ValueCountFrequency (%)
157959
18.1%
042088
13.1%
240323
12.6%
733506
10.5%
329447
9.2%
826684
8.3%
925314
7.9%
523012
 
7.2%
422979
 
7.2%
618834
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
-326
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4422094
93.2%
Common320472
 
6.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e483062
 
10.9%
a352741
 
8.0%
r334889
 
7.6%
o287844
 
6.5%
n255802
 
5.8%
i241118
 
5.5%
t210878
 
4.8%
s200749
 
4.5%
l189968
 
4.3%
d147651
 
3.3%
Other values (42)1717392
38.8%
Common
ValueCountFrequency (%)
157959
18.1%
042088
13.1%
240323
12.6%
733506
10.5%
329447
9.2%
826684
8.3%
925314
7.9%
523012
 
7.2%
422979
 
7.2%
618834
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII4742566
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e483062
 
10.2%
a352741
 
7.4%
r334889
 
7.1%
o287844
 
6.1%
n255802
 
5.4%
i241118
 
5.1%
t210878
 
4.4%
s200749
 
4.2%
l189968
 
4.0%
d147651
 
3.1%
Other values (53)2037864
43.0%

review_aroma
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.817350199
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 MiB
2022-07-29T19:32:54.640500image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q13.5
median4
Q34.5
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7189030162
Coefficient of variation (CV)0.1883251414
Kurtosis1.386830168
Mean3.817350199
Median Absolute Deviation (MAD)0.5
Skewness-0.9745390733
Sum2018882
Variance0.5168215467
MonotonicityNot monotonic
2022-07-29T19:32:54.736581image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4182294
34.5%
4.5116460
22.0%
3.5106232
20.1%
353495
 
10.1%
529031
 
5.5%
2.521060
 
4.0%
213013
 
2.5%
1.54446
 
0.8%
12839
 
0.5%
ValueCountFrequency (%)
12839
 
0.5%
1.54446
 
0.8%
213013
 
2.5%
2.521060
 
4.0%
353495
 
10.1%
3.5106232
20.1%
4182294
34.5%
4.5116460
22.0%
529031
 
5.5%
ValueCountFrequency (%)
529031
 
5.5%
4.5116460
22.0%
4182294
34.5%
3.5106232
20.1%
353495
 
10.1%
2.521060
 
4.0%
213013
 
2.5%
1.54446
 
0.8%
12839
 
0.5%

review_text
Categorical

HIGH CARDINALITY
UNIFORM

Distinct528371
Distinct (%)99.9%
Missing119
Missing (%)< 0.1%
Memory size4.0 MiB
#NAME?
 
92
Pours a light yellow color, nice carbonation, small white head, with some sticky lacing left behind. The nose is malty, with some hops, slight caramel. The taste is slightly sweet, malty, slight hop note. Light body. Not drinkable, would not buy again.
 
10
Cute 250ml Kiddy cans ( hide em in yer jeans from teacher)noxious sweet kiddy taste (Hides the alcohol well that you intend to get gooned on)_.seems like another winning marketing device for Molson who have staked out the kiddy market for their own. Nothing special or note worthy about this beverage (I say beverage because it has as little in common with real beer as a soft drink) with the exception of warnings on the can to serve extremely chilled..I can see my gag reflex kicking in if I had to drink this Popsicle-sweet green beer at room temp. Bland pale yellow appeance..no head or aromas to speak of and a sweet corn taste devoid of hops with an indescribably annoying sweet after taste (corn syrup mixed with stale chip oil is the closest I can come in description) The typical mega brewer let down in the taste department is not the real story here. I think the mindset behind the kiddy kan (250ml) the 6% ABV and the 4-pack is a priceless statement on the devolution of mass Canadian beer marketing politics. They obviously see the kiddies (teens and arrested development twenty-somethings as the main market for their mass produced slop but they must salve their federal nannies who pay lip service to the tragedy of teen addictions and auto deaths (Yet the feds profit handsomely from the arrangement via booze tax and monopoly alcohol sales) So they show good corporate citizenship by packaging their little kiddy alcohol bombers in small 2 gulp cans and 4-packs (and sell more units for teens hungry to get gooned on this wobbly pop)classic modern Canadian compromise of a once proud brewing tradition. If you guzzle 8 of these buzz bombs before the Averil concert try not to yak on your crew of fall off something high or wet the bed when you pass out.lets be careful eh?drink a lot but dont blame us eh?
 
3
NIce stout, although can be considered and it is catalogued as a porter. ANyway, the foam is great, it sticks to the glass as it has to, and its colour is not white as most of the beers. IT has a toasted grains flavor I like, and it is not as tiring as other beers of this style.
 
3
Sort of a typical pale lager that tried to be better - without success. Pours a light yellow, with a small, close to a 1/2 finger head. Their is a ring of lace at the top, where when you first pour the beer the head settles. Nothing underneath that. Not much of a smell. Bit of hops, some malt, and a little more bittering. Light taste. Sort of a mellow sweetness, mingled with a dry bitterness. Mouthfeel is light, like water. But, it is drinkable and it is thirst quenching. Extra half point for that.
 
3
Other values (528366)
528640 

Length

Max length4992
Median length3329
Mean length690.6486588
Min length6

Characters and Unicode

Total characters365181169
Distinct characters98
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique528094 ?
Unique (%)99.9%

Sample

1st rowA lot of foam. But a lot. In the smell some banana, and then lactic and tart. Not a good start. Quite dark orange in color, with a lively carbonation (now visible, under the foam). Again tending to lactic sourness. Same for the taste. With some yeast and banana.
2nd rowDark red color, light beige foam, average. In the smell malt and caramel, not really light. Again malt and caramel in the taste, not bad in the end. Maybe a note of honey in teh back, and a light fruitiness. Average body. In the aftertaste a light bitterness, with the malt and red fruit. Nothing exceptional, but not bad, drinkable beer.
3rd rowAlmost totally black. Beige foam, quite compact, not bad. Light smell, just a bit of roast, and some hop. A bit too light. The taste is light oo, and drinkable, with some malt, roast, hints of coffee. Nothing exceptional, but after all drinkable and pleasant. Light to average body. In the aftertaste some dust, somr roast, hint of caramel, and a bit of bitterness. No defect, drinkable, not bad.
4th rowGolden yellow color. White, compact foam, quite creamy. Good appearance. Fresh smell, with good hop. Quite dry, with a good grassy note. Hay. Fresh and pleasant. More sweet in the mouth, with honey. The hop comes back in the end, and in the aftertaste. Not bad, but a bit too sweet for a pils. In the end some vanilla and camomile note. In the aftertaste, too. Though the hop, a bit too sweet. Honest.
5th rowAccording to the website, the style for the Caldera Cauldron changes every year. The current release is a DIPA, which frankly is the only cauldron I'm familiar with (it was an IPA/DIPA the last time I ordered a cauldron at the horsebrass several years back). In any event... at the Horse Brass yesterday. The beer pours an orange copper color with good head retention and lacing. The nose is all hoppy IPA goodness, showcasing a huge aroma of dry citrus, pine and sandlewood. The flavor profile replicates the nose pretty closely in this West Coast all the way DIPA. This DIPA is not for the faint of heart and is a bit much even for a hophead like myslf. The finish is quite dry and hoppy, and there's barely enough sweet malt to balance and hold up the avalanche of hoppy bitterness in this beer. Mouthfeel is actually fairly light, with a long, persistentely bitter finish. Drinkability is good, with the alcohol barely noticeable in this well crafted beer. Still, this beer is so hugely hoppy/bitter, it's really hard for me to imagine ordering more than a single glass. Regardless, this is a very impressive beer from the folks at Caldera.

Common Values

ValueCountFrequency (%)
#NAME?92
 
< 0.1%
Pours a light yellow color, nice carbonation, small white head, with some sticky lacing left behind. The nose is malty, with some hops, slight caramel. The taste is slightly sweet, malty, slight hop note. Light body. Not drinkable, would not buy again.10
 
< 0.1%
Cute 250ml Kiddy cans ( hide em in yer jeans from teacher)noxious sweet kiddy taste (Hides the alcohol well that you intend to get gooned on)_.seems like another winning marketing device for Molson who have staked out the kiddy market for their own. Nothing special or note worthy about this beverage (I say beverage because it has as little in common with real beer as a soft drink) with the exception of warnings on the can to serve extremely chilled..I can see my gag reflex kicking in if I had to drink this Popsicle-sweet green beer at room temp. Bland pale yellow appeance..no head or aromas to speak of and a sweet corn taste devoid of hops with an indescribably annoying sweet after taste (corn syrup mixed with stale chip oil is the closest I can come in description) The typical mega brewer let down in the taste department is not the real story here. I think the mindset behind the kiddy kan (250ml) the 6% ABV and the 4-pack is a priceless statement on the devolution of mass Canadian beer marketing politics. They obviously see the kiddies (teens and arrested development twenty-somethings as the main market for their mass produced slop but they must salve their federal nannies who pay lip service to the tragedy of teen addictions and auto deaths (Yet the feds profit handsomely from the arrangement via booze tax and monopoly alcohol sales) So they show good corporate citizenship by packaging their little kiddy alcohol bombers in small 2 gulp cans and 4-packs (and sell more units for teens hungry to get gooned on this wobbly pop)classic modern Canadian compromise of a once proud brewing tradition. If you guzzle 8 of these buzz bombs before the Averil concert try not to yak on your crew of fall off something high or wet the bed when you pass out.lets be careful eh?drink a lot but dont blame us eh?3
 
< 0.1%
NIce stout, although can be considered and it is catalogued as a porter. ANyway, the foam is great, it sticks to the glass as it has to, and its colour is not white as most of the beers. IT has a toasted grains flavor I like, and it is not as tiring as other beers of this style.3
 
< 0.1%
Sort of a typical pale lager that tried to be better - without success. Pours a light yellow, with a small, close to a 1/2 finger head. Their is a ring of lace at the top, where when you first pour the beer the head settles. Nothing underneath that. Not much of a smell. Bit of hops, some malt, and a little more bittering. Light taste. Sort of a mellow sweetness, mingled with a dry bitterness. Mouthfeel is light, like water. But, it is drinkable and it is thirst quenching. Extra half point for that.3
 
< 0.1%
I really do not care for this beer or any molson beer, it gives me really bad gas. Light color and body with no hops or malt just a bunch of corn and rice. My mother in law comes and she brings the crap, so i have to drink it and my wife puts up with the gas.3
 
< 0.1%
It poured a copper color with a nice white head. It has a very strong malt smell and flavor. It was a lot sweeter than I was expecting. There was a little bit of the alcohol coming through at the end. It had a nice creamy mouthfeel. One I would drink again if they were to make it again.3
 
< 0.1%
Pours a darker amber color, white head dissipates quickly. It has a strange aroma, not sure how to describe it, but its malty. Flavor is bread like, almost toasty malts. No significant hop flavors. Medium mouthfeel. This would make a nice session beer, good flavor but nothing too exciting.2
 
< 0.1%
Semi opaque burnt orange pour in a tulip. Thick, lump head dissipated pretty quickly. Looks like a classic SN...beautiful for about 30 seconds, then well, messy. Spicy and very bright and floral in the nose (high grade marijuana buds) with malts present in the background. Dried fruits and spices...Big fruity hops are abundant. Earthy and grainy, the barley malts add a depth that surround the huge amount of hops beautifully. Pine nuts and a tangy finish. Dense, oily feel foamy on the tongue. This beer is really good. It really has the depth and hops of a double IPA. This is a well named brew. Tastes and feels like a harvest. Pairs nicely with turkey and cranberry salad. This is my second bottle this autumn and hope to have more. Great!2
 
< 0.1%
This is Spinnakers 20th Annie beer. on the pour: looks light for an Ale..pale light gold with a white head,fads fast with little lacing,but the nose on pour was great,flowers and hops. On taste Citrus,and malt on start,Then ginger and lemon grass,malts and hops in the finish,a real nice beer. good body,it sort of coats the tongue in a good way,and lingers on as lemon.2
 
< 0.1%
Other values (528361)528628
> 99.9%
(Missing)119
 
< 0.1%

Length

2022-07-29T19:32:54.952360image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
a3230379
 
4.9%
the2795428
 
4.3%
and1992960
 
3.0%
of1635203
 
2.5%
is1303889
 
2.0%
with1203087
 
1.8%
to978127
 
1.5%
this911742
 
1.4%
i862812
 
1.3%
it836693
 
1.3%
Other values (366471)49641917
75.9%

Most occurring characters

ValueCountFrequency (%)
64863522
17.8%
e32446750
 
8.9%
t26850996
 
7.4%
a23987947
 
6.6%
o20999806
 
5.8%
i19765294
 
5.4%
s18093609
 
5.0%
n16723594
 
4.6%
r16448787
 
4.5%
l14724529
 
4.0%
Other values (88)110276335
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter277752632
76.1%
Space Separator64863522
 
17.8%
Other Punctuation11322755
 
3.1%
Uppercase Letter8910889
 
2.4%
Decimal Number1055214
 
0.3%
Dash Punctuation938238
 
0.3%
Close Punctuation150660
 
< 0.1%
Open Punctuation145871
 
< 0.1%
Math Symbol20819
 
< 0.1%
Currency Symbol18299
 
< 0.1%
Other values (3)2270
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e32446750
11.7%
t26850996
 
9.7%
a23987947
 
8.6%
o20999806
 
7.6%
i19765294
 
7.1%
s18093609
 
6.5%
n16723594
 
6.0%
r16448787
 
5.9%
l14724529
 
5.3%
h14160299
 
5.1%
Other values (16)73551021
26.5%
Uppercase Letter
ValueCountFrequency (%)
I1469955
16.5%
T1351847
15.2%
A984439
11.0%
S746217
 
8.4%
P508791
 
5.7%
M488002
 
5.5%
B425726
 
4.8%
D360003
 
4.0%
N323598
 
3.6%
C287848
 
3.2%
Other values (16)1964463
22.0%
Other Punctuation
ValueCountFrequency (%)
.5881831
51.9%
,3374886
29.8%
'809814
 
7.2%
:533518
 
4.7%
/200242
 
1.8%
!148372
 
1.3%
"130382
 
1.2%
;77365
 
0.7%
?61207
 
0.5%
%49447
 
0.4%
Other values (5)55691
 
0.5%
Decimal Number
ValueCountFrequency (%)
2226225
21.4%
1225275
21.3%
0200033
19.0%
5100110
9.5%
460717
 
5.8%
359965
 
5.7%
953739
 
5.1%
748681
 
4.6%
640880
 
3.9%
839589
 
3.8%
Control
ValueCountFrequency (%)
4
50.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%
1
 
12.5%
Math Symbol
ValueCountFrequency (%)
=9730
46.7%
+6341
30.5%
~2663
 
12.8%
|2085
 
10.0%
Close Punctuation
ValueCountFrequency (%)
)148753
98.7%
]1827
 
1.2%
}80
 
0.1%
Open Punctuation
ValueCountFrequency (%)
(143933
98.7%
[1854
 
1.3%
{84
 
0.1%
Modifier Symbol
ValueCountFrequency (%)
`324
61.2%
^205
38.8%
Space Separator
ValueCountFrequency (%)
64863522
100.0%
Dash Punctuation
ValueCountFrequency (%)
-938238
100.0%
Currency Symbol
ValueCountFrequency (%)
$18299
100.0%
Connector Punctuation
ValueCountFrequency (%)
_1733
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin286663521
78.5%
Common78517648
 
21.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e32446750
 
11.3%
t26850996
 
9.4%
a23987947
 
8.4%
o20999806
 
7.3%
i19765294
 
6.9%
s18093609
 
6.3%
n16723594
 
5.8%
r16448787
 
5.7%
l14724529
 
5.1%
h14160299
 
4.9%
Other values (42)82461910
28.8%
Common
ValueCountFrequency (%)
64863522
82.6%
.5881831
 
7.5%
,3374886
 
4.3%
-938238
 
1.2%
'809814
 
1.0%
:533518
 
0.7%
2226225
 
0.3%
1225275
 
0.3%
/200242
 
0.3%
0200033
 
0.3%
Other values (36)1264064
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII365181169
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64863522
17.8%
e32446750
 
8.9%
t26850996
 
7.4%
a23987947
 
6.6%
o20999806
 
5.8%
i19765294
 
5.4%
s18093609
 
5.0%
n16723594
 
4.6%
r16448787
 
4.5%
l14724529
 
4.0%
Other values (88)110276335
30.2%
Distinct527927
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size4.0 MiB
Minimum1998-01-10 00:00:01
Maximum2012-01-11 10:10:56
2022-07-29T19:32:55.100877image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:55.229564image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

review_year
Real number (ℝ≥0)

HIGH CORRELATION

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2008.307208
Minimum1998
Maximum2012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 MiB
2022-07-29T19:32:55.343005image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1998
5-th percentile2003
Q12007
median2009
Q32010
95-th percentile2011
Maximum2012
Range14
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.409738716
Coefficient of variation (CV)0.001199885509
Kurtosis-0.268179069
Mean2008.307208
Median Absolute Deviation (MAD)2
Skewness-0.7624986439
Sum1062133433
Variance5.80684068
MonotonicityNot monotonic
2022-07-29T19:32:55.438401image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2011110836
21.0%
201093810
17.7%
200983578
15.8%
200869080
13.1%
200746514
8.8%
200643083
 
8.1%
200529433
 
5.6%
200422905
 
4.3%
200318187
 
3.4%
20027581
 
1.4%
Other values (5)3863
 
0.7%
ValueCountFrequency (%)
199823
 
< 0.1%
199925
 
< 0.1%
200033
 
< 0.1%
2001602
 
0.1%
20027581
 
1.4%
200318187
 
3.4%
200422905
4.3%
200529433
5.6%
200643083
8.1%
200746514
8.8%
ValueCountFrequency (%)
20123180
 
0.6%
2011110836
21.0%
201093810
17.7%
200983578
15.8%
200869080
13.1%
200746514
8.8%
200643083
 
8.1%
200529433
 
5.6%
200422905
 
4.3%
200318187
 
3.4%

review_month
Real number (ℝ≥0)

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.614686029
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 MiB
2022-07-29T19:32:55.544080image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median7
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.523104765
Coefficient of variation (CV)0.5326185929
Kurtosis-1.253343062
Mean6.614686029
Median Absolute Deviation (MAD)3
Skewness-0.04719774764
Sum3498309
Variance12.41226718
MonotonicityNot monotonic
2022-07-29T19:32:55.634391image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1249993
9.5%
1147518
9.0%
146992
8.9%
845409
8.6%
1045356
8.6%
344257
8.4%
943268
8.2%
542692
8.1%
741816
7.9%
241304
7.8%
Other values (2)80265
15.2%
ValueCountFrequency (%)
146992
8.9%
241304
7.8%
344257
8.4%
440341
7.6%
542692
8.1%
639924
7.5%
741816
7.9%
845409
8.6%
943268
8.2%
1045356
8.6%
ValueCountFrequency (%)
1249993
9.5%
1147518
9.0%
1045356
8.6%
943268
8.2%
845409
8.6%
741816
7.9%
639924
7.5%
542692
8.1%
440341
7.6%
344257
8.4%

review_hr
Real number (ℝ≥0)

ZEROS

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.42443701
Minimum0
Maximum23
Zeros43762
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size4.0 MiB
2022-07-29T19:32:55.737304image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median8
Q319
95-th percentile23
Maximum23
Range23
Interquartile range (IQR)17

Descriptive statistics

Standard deviation8.440870876
Coefficient of variation (CV)0.8097195916
Kurtosis-1.63302332
Mean10.42443701
Median Absolute Deviation (MAD)7
Skewness0.1925083438
Sum5513172
Variance71.24830114
MonotonicityNot monotonic
2022-07-29T19:32:55.842643image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
148790
 
9.2%
248289
 
9.1%
043762
 
8.3%
342732
 
8.1%
2337067
 
7.0%
432984
 
6.2%
2232082
 
6.1%
2127408
 
5.2%
2025088
 
4.7%
1923338
 
4.4%
Other values (14)167330
31.6%
ValueCountFrequency (%)
043762
8.3%
148790
9.2%
248289
9.1%
342732
8.1%
432984
6.2%
522774
4.3%
614777
 
2.8%
79518
 
1.8%
86247
 
1.2%
94153
 
0.8%
ValueCountFrequency (%)
2337067
7.0%
2232082
6.1%
2127408
5.2%
2025088
4.7%
1923338
4.4%
1820989
4.0%
1718627
3.5%
1616498
3.1%
1514905
2.8%
1413001
 
2.5%

Interactions

2022-07-29T19:32:45.059979image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:17.394870image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:20.143765image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:22.809653image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:26.588387image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:29.109645image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:31.854627image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:34.453307image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:37.070247image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:39.703175image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:42.515553image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:45.298791image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:17.657190image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:20.398024image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:23.044132image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:26.820169image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:29.345844image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:32.093030image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:34.682173image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:37.318409image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:39.943194image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:42.755041image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:45.534945image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:17.907753image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:20.652790image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:24.576998image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:27.057648image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:29.579661image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:32.335765image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:34.924201image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:37.559043image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:40.186417image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:42.992967image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:45.761732image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:18.154602image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:20.888936image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:24.795662image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:27.274373image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:29.814858image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:32.575471image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:35.159028image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:37.797980image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:40.418951image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:43.219208image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:45.986269image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:18.406183image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:21.124619image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:25.011607image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:27.501948image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:30.040709image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:32.805429image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:35.390698image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:38.031206image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:40.834402image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:43.441664image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:46.224777image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:18.672260image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:21.374629image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:25.235803image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:27.742042image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:30.284323image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:33.039116image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:35.635317image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:38.280314image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:41.073091image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:43.677338image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:46.452517image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:18.918862image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:21.603406image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:25.447485image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:27.953821image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:30.510001image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:33.281166image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:35.868735image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:38.517987image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:41.308156image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:43.903899image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:46.688019image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:19.174619image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:21.851709image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:25.673999image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:28.190134image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:30.750395image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:33.521842image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:36.115891image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:38.756718image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:41.569889image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:44.137516image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:46.936790image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:19.424191image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:22.100241image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:25.902824image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:28.424867image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:30.990106image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:33.768238image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:36.360026image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:39.019862image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:41.809591image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:44.370337image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:47.189199image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:19.671125image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:22.340606image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:26.130741image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:28.662226image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:31.228730image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:34.002133image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:36.595702image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:39.248940image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:42.056071image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:44.599314image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:47.411958image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:19.913288image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:22.575719image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:26.355492image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:28.885048image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:31.455880image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:34.230064image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:36.834140image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:39.478544image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:42.287164image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-07-29T19:32:44.832330image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-07-29T19:32:55.940901image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-07-29T19:32:56.113640image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-07-29T19:32:56.282140image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-07-29T19:32:56.448494image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-07-29T19:32:48.106377image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2022-07-29T19:32:49.243921image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-07-29T19:32:50.929044image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-07-29T19:32:51.509075image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

beer_ABVbeer_beerIdbeer_brewerIdbeer_namebeer_stylereview_appearancereview_palettereview_overallreview_tastereview_profileNamereview_aromareview_textreview_timereview_yearreview_monthreview_hr
05.04798610325Sausa WeizenHefeweizen2.52.01.51.5stcules1.5A lot of foam. But a lot. In the smell some banana, and then lactic and tart. Not a good start. Quite dark orange in color, with a lively carbonation (now visible, under the foam). Again tending to lactic sourness. Same for the taste. With some yeast and banana.2009-02-16 20:57:032009220
16.24821310325Red MoonEnglish Strong Ale3.02.53.03.0stcules3.0Dark red color, light beige foam, average. In the smell malt and caramel, not really light. Again malt and caramel in the taste, not bad in the end. Maybe a note of honey in teh back, and a light fruitiness. Average body. In the aftertaste a light bitterness, with the malt and red fruit. Nothing exceptional, but not bad, drinkable beer.2009-03-01 13:44:572009313
26.54821510325Black Horse Black BeerForeign / Export Stout3.02.53.03.0stcules3.0Almost totally black. Beige foam, quite compact, not bad. Light smell, just a bit of roast, and some hop. A bit too light. The taste is light oo, and drinkable, with some malt, roast, hints of coffee. Nothing exceptional, but after all drinkable and pleasant. Light to average body. In the aftertaste some dust, somr roast, hint of caramel, and a bit of bitterness. No defect, drinkable, not bad.2009-03-01 14:10:042009314
35.04796910325Sausa PilsGerman Pilsener3.53.03.02.5stcules3.0Golden yellow color. White, compact foam, quite creamy. Good appearance. Fresh smell, with good hop. Quite dry, with a good grassy note. Hay. Fresh and pleasant. More sweet in the mouth, with honey. The hop comes back in the end, and in the aftertaste. Not bad, but a bit too sweet for a pils. In the end some vanilla and camomile note. In the aftertaste, too. Though the hop, a bit too sweet. Honest.2009-02-15 19:12:252009219
47.7648831075Cauldron DIPAAmerican Double / Imperial IPA4.04.54.04.0johnmichaelsen4.5According to the website, the style for the Caldera Cauldron changes every year. The current release is a DIPA, which frankly is the only cauldron I'm familiar with (it was an IPA/DIPA the last time I ordered a cauldron at the horsebrass several years back). In any event... at the Horse Brass yesterday. The beer pours an orange copper color with good head retention and lacing. The nose is all hoppy IPA goodness, showcasing a huge aroma of dry citrus, pine and sandlewood. The flavor profile replicates the nose pretty closely in this West Coast all the way DIPA. This DIPA is not for the faint of heart and is a bit much even for a hophead like myslf. The finish is quite dry and hoppy, and there's barely enough sweet malt to balance and hold up the avalanche of hoppy bitterness in this beer. Mouthfeel is actually fairly light, with a long, persistentely bitter finish. Drinkability is good, with the alcohol barely noticeable in this well crafted beer. Still, this beer is so hugely hoppy/bitter, it's really hard for me to imagine ordering more than a single glass. Regardless, this is a very impressive beer from the folks at Caldera.2010-12-30 18:53:2620101218
54.7521591075Caldera Ginger BeerHerbed / Spiced Beer3.53.53.03.0oline733.5Poured from the bottle into a Chimay goblet. Appearance: Pours a slightly cloudy yellow/orange color with a half finger of fluffy white head. The head fades to a small layer on top of the pour. Smell: Very light and crisp. I'm definitely picking up the ginger, but it's not overly powerful. There is a slight sweetness from the malt as well. Taste: Very light and refreshing. The ginger shows up right away and then fades towards the finish of the sip. The finish is malty and bread like. Mouthfeel: The body is on the thin side with smooth carbonation and a very dry finish. Overall: This is a light and refreshing beer, but nothing spectacular. The amount of ginger is nice, but I would have liked to have more going on.2012-01-02 17:17:392012117
64.7521591075Caldera Ginger BeerHerbed / Spiced Beer3.53.53.54.0Reidrover4.022 oz bottle from "Lifesource" Salem. $3.95 Nice golden clear beer body with a nice sized frothy/creamy white head. Ok aromas..mainlly a bit of ginger speice and some bready malt..simple nice Taste very nice indeed..nice spicy ginger backed with slightly caramel maltiness..simple again but i like . Liked the mouthfeel of this one..very forward carbonation which helps the ginger effect and a lingering ginger in the after taste. Overall a simple ginger brew .I liked it2011-10-19 02:25:152011102
74.7521591075Caldera Ginger BeerHerbed / Spiced Beer3.52.53.02.0alpinebryant3.5Bottle says "Malt beverage brewed with Ginger and ginger added" Sounds redundant to me, but lets move on. Pours a bud light yellow with a tiny white head of small bubbles. The beer is almost as clear as a glass of water with some food coloring in it. Aroma of light ginger, a very light malt aroma but primarily odorless on the malt side. I wouldn't be completely surprised if there were some adjuncts in here because of the lack of underlying malt flavors. Taste is of a light adjunct lager with a dosing of ginger. Not surprising there. This is a light session beer, good for the warmer days of spring / summer. Mouthfeel is extremely light, high carbonation. Overall decent. This would be great if you were drinking beers on draft at the bar with some friends just hanging out. I wouldn't necessarily seek it out though to drink out of a bottle.2011-05-24 22:26:582011522
84.7521591075Caldera Ginger BeerHerbed / Spiced Beer3.53.04.03.5LordAdmNelson4.0I'm not sure why I picked this up... I like ginger, and it was reasonably cheap compared to the other beers I was looking at. Pours a pale golden color with smallish head. Nose is largely uneventful, some ginger in there, a bit of pear, but mainly normal lager. Taste is pretty good, bringing a bit more of the ginger to the fore. MF was a bit fizzy, not terrible though. Easy drinker, I had no problem finishing the bomber. Interesting, but I probably won't get it again.2010-11-22 19:35:0320101119
94.7521591075Caldera Ginger BeerHerbed / Spiced Beer5.03.54.54.0augustgarage4.0Poured from a 22oz bomber into my Drie Fonteinen tumbler. Hazy titanium yellow body (which catches the shadows forming a beautiful mysterious gradient) with an incredibly dense pillow of magnolia cream. Heavy persistent head and rich creamy lacing. Pale malt, asian pear, and a hint of citrus in the nose. A vaguely tropical lager... Tastes very much like a well done APA, with a nice balance of pale malt and low hop bitterness. The ginger adds to the refreshing character, but isn't readily detectable at first (lacks any "bite"). Medium-dry finish - very clean and extremely quaffable. I can imagine hibiscus and beets working in small quantities, though I think they omitted those for this version... Light bodied, pillowy, smooth and moderately carbonated. Don't go into this expecting a ginger beer (despite its name) as it has little in common with that spicy soft drink. This is a wonderful session ale though, and worth seeking out if you are a fan of light yet flavorful lagers. Would obviously go perfectly with sushi.2010-09-28 00:15:24201090

Last rows

beer_ABVbeer_beerIdbeer_brewerIdbeer_namebeer_stylereview_appearancereview_palettereview_overallreview_tastereview_profileNamereview_aromareview_textreview_timereview_yearreview_monthreview_hr
528860NaN40323340Dinkel Acker DarkMunich Dunkel Lager3.53.53.53.0gmfessen3.5Poured from the bottle into a pint glass, beer is a deep ruby-crimson color with a thin, almost stagnant head. The smell is malt dominate, slight toasted and caramel notes coming through. The taste is very similar, very malt forward - slightly skunked (probably due to the green bottle). The mouthfeel is medium in body and under carbonated. Overall, a drinkable beer - decent but nothing spectacular.2008-07-06 02:35:45200872
528861NaN40323340Dinkel Acker DarkMunich Dunkel Lager3.02.02.02.5xare2.5Pours as a dark mahogany with about 1/8" of tan foam that laces somewhat decently. Average in appearance. Smell was of musky wet malts, hops, and skunk. While not totally offputting, somewhat strange. Taste was almost like an Oktoberfest brew but somewhat lighter and skunkier. Overall, not impressed with the flavor. Mouthfeel was somewhat bland and I can't really find the words to describe it - it has a bit of carbonation that goes away rather fast and not much else's left. Drinkability wasn't going to score high. I wouldn't search this beer out and probably wouldn't drink it if offered for free.2008-06-29 17:52:582008617
528862NaN40323340Dinkel Acker DarkMunich Dunkel Lager3.53.54.04.0animal694.5i haven't had one of these for a while ; pours a med-dark copper brown w/ a thin off-white head which dissipates almost immediatly leaving a decent lacing in my nonic ; a nutty, metallic smell, a bit of fig or some darker fruit as well ; a crisp, malty flavor from the onset, mostly an all grain bread w/ some more dark fruit undertones, a decent, slightly sweet finish w/ a bit of metal in it as well ; a light, dry brew w/ a good amount of co2 letting the flavor linger a while ; a very drinkable one, i've always thought this an excellent dunkel...2008-04-06 01:38:11200841
528863NaN40323340Dinkel Acker DarkMunich Dunkel Lager3.03.52.52.5pmcadamis3.0A - A beige one finger head sits atop a rootbeer colored brew that shows some crimson highlights, and can look almost purple at times. The head fades relatively quickly, and only a little bit of spotty lace is left on the glass. Swirling brings a little bit of head back up, but it's short-lived. S - Rootbeer and caramel are the major players here, accompanied by some black licorice and sugar cane. Some gentle grapey notes are there too. This is mild, fresh, and sweet to my nose. T - Sweet brown sugar and caramel dominate this brew. Gentle, mild, fresh, and slightly fruity. There is a low-level of buttered toast diacetyls that I really like, and there is a big similarity to cola. M - Light bodied, gently carbonated, and slightly sweet at the finish. Sort of like flat Pepsi. D - Not a bad beer. Too sweet and cola-like IMO, but could be a good choice for a summer session when a dark beer is called for.2008-03-29 18:40:022008318
528864NaN40323340Dinkel Acker DarkMunich Dunkel Lager4.04.04.04.0Greggy4.0Appearance- A very nice ruby brown color pours a 2 finger head that recedes to a nice thin head. Smell- At first sniff, I gather notes, bready, banana, but I also gather a very fresh flour smell. Taste- Sweet dark candies come through with a light amount of sweet pinnaple and dark malts. It's a very interesting sweet malt. Also, the fresh flour is evident in the finish. Mouthfeel- Lightly carbonated which works nicely with the style. Drinkability- This is a pretty interesting dunkel lager and unlike any other I have tried. I may revisit it in the future.2008-03-20 03:47:33200833
528865NaN40323340Dinkel Acker DarkMunich Dunkel Lager4.03.04.03.5orangemoustache4.0A-pours a reddish amber that looks very nice,lots of thick almond head hides quickly leaving very trace amounts of lacing S-not very strong in this area...some caramel sweetness is followed by grainy notes T-wheat bread, honey,sugary sweet caramel,slight pine like bitterness from hops on the tail M-light body helps drinkability but leaves much to be desired,carbonation is about right,dryness in the middle that continues till the finish and beyond D- less complexity than other Dunkels helps it go down quite easily and without much thought because of it well rounded simplicity2008-03-11 05:18:41200835
528866NaN40323340Dinkel Acker DarkMunich Dunkel Lager4.03.53.03.0MisterStout3.0I don't really have anything special to say about this one. I felt it was far too thin, didn't have enough hop character, and was too sweet compared to the other Dunkels I've had. It sure is pretty in a pint glass, though. Great amber color. Not terrible. I definitely wouldn't turn it down if offered at a party.2008-02-20 06:59:43200826
528867NaN40323340Dinkel Acker DarkMunich Dunkel Lager4.04.04.54.0meechum4.5Had this on tap at Vreny's Beirgarten A - Came to the table with in a mug. Amber/copper color with a nice fluffy white head that fell slowly and left a nice lace down the glass S - The smell was very bready and nutty along with a hint of caramel T/M - Very much like the smell but bigger..had a very bready taste with hints of a nutty taste and then just a bit of floral hops on the end to give it some spice. The mouthfeel was slick and well carbonated without being too carbonated D - I had close to 48 oz of this brew tonight before, during and after dinner and it really never hit me so I'm not sure exactly what the ABV is but I don't think it's above 5.5 or 5.9 tops. Overall it is a very drinkable brew in my opinion and I enjoyed it very much..I would consider this one of the better beers I've had an opportunity to taste2008-01-26 04:14:57200814
528868NaN40323340Dinkel Acker DarkMunich Dunkel Lager4.03.04.04.0Dodo2step4.5Purchased at Market Cross Pub in carlisle, PA. My one friend tells me his dad used to drink this in the 80's. I have never heard of it until now. A-After pouring it has a lil tan colored head but not toomuch to be excited about. It looks like creamy dark chocolate. T-it kind has a cross between a yuengling lager taste and a bud light. Sweet yet bitter. M-feels kind of forthy in the mouth and quite tasty and sweet. D-It would definitely be worth to buy a six pack of this beer. Never heard of it but it is pretty good.2008-01-24 22:54:502008122
528869NaN40323340Dinkel Acker DarkMunich Dunkel Lager4.04.04.04.0jenbys20014.0I ordered a mug of this beer at Schnitzelhaus, a local German restaurant, here in Tampa. The beer was very dark in the glass, and actually looked similar to root beer with a small frothy head. It had a nice spicy caramel smell, with hints of apple. It was a medium bodied beer with a hoppy finish. However the hoppy taste was not overbearing, so overall it was very drinkable beer. I really enjoyed it and felt it was a good representation of beers I drank while in Germany.2008-01-14 18:46:072008118